Digital images are made up of pixels having multiple components such as color and intensity that are uniquely defined for different image types. For example, binary digital images have bi-level values, i.e., two possible values, for each pixel, namely, black (represented by the number “1”) or white (represented by the number “0”). On the other hand, grayscale or continuous tone digital images have multiple bits per pixel, such as 8-bit value per pixel comprising 256 tones or shades of gray for each pixel in the image (gray levels of 0 to 255). Such bi-level pixels or multiple-bit pixels are represented by color planes in color images, where the pixels of different component colors are combined on a print medium, for example, a paper, to form a dot. The dot color represents a combination of tone values in different color planes.
Various conditions and/or scenarios may be relevant to the printing of lines or curves that may be only one or two pixels in width. Often, printers, plotters, or other printing devices that transfer data or images onto a print medium are required to print curved or straight thin lines that may only be partially visible on a print medium at certain resolutions (depending on the printing device) due to operational dot gain and dot loss of the printing device. Existing methods for thin-line enhancement include template-matching to detect thin lines that are dependent on halftone growth, halftone frequency, and printer resolution. Such dependencies increase the computation load on the printer processor, which lowers efficiency resulting in longer print times, and may not consistently enhance thin lines at the pixel level of resolution. Other thin-line enhancement methods, such as those based on tone response curve (TRC) of each pixel, are prone to introduce artifacts across the entire print medium during a print operation. In other words, prior methods of thin-line enhancement are susceptible to unwanted merging of two or more thin-lines with each another or an adjacent line in close proximity during thin-line width enhancement.
Thus, it would be advantageous to provide a computationally efficient and thin-line enhancement method that avoids merging of thin lines with neighboring pixels in an image.